CrunchBase Scrapper collects structured company information from Crunchbase pages in real time. It helps teams transform scattered company profiles into clean, analyzable datasets for research and growth intelligence.
Created by Bitbash, built to showcase our approach to Scraping and Automation!
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This project extracts detailed company-level data from Crunchbase and converts it into structured records ready for analysis. It solves the problem of manual data collection from dynamic company pages and is built for analysts, founders, and growth teams.
- Processes single-page company profiles with consistent structure
- Converts unstructured HTML into clean, usable data fields
- Designed for scalable research and competitive analysis
- Easily adaptable to new company attributes and layouts
| Feature | Description |
|---|---|
| Real-time extraction | Fetches up-to-date company information from live pages. |
| Structured output | Normalizes company data into consistent records. |
| Flexible parsing | Easily extend field extraction logic as needs evolve. |
| Lightweight architecture | Minimal dependencies with efficient request handling. |
| Data-ready format | Output is optimized for analytics and downstream systems. |
| Field Name | Field Description |
|---|---|
| company_name | Official name of the company. |
| website | Primary company website URL. |
| description | Short company overview or summary. |
| industry | Main industry or sector classification. |
| headquarters | Location of company headquarters. |
| founded_year | Year the company was founded. |
| funding_stage | Latest known funding stage. |
| total_funding | Total disclosed funding amount. |
[
{
"company_name": "Example Corp",
"website": "https://www.example.com",
"description": "A technology company focused on data analytics solutions.",
"industry": "Software",
"headquarters": "San Francisco, CA, USA",
"founded_year": 2018,
"funding_stage": "Series B",
"total_funding": "$45M"
}
]
CrunchBase Scrapper/
├── src/
│ ├── runner.py
│ ├── fetcher.py
│ ├── parser.py
│ └── utils.py
├── data/
│ ├── input.example.json
│ └── sample_output.json
├── requirements.txt
└── README.md
- Startup founders use it to analyze competitors, so they can position their products strategically.
- Investors use it to research companies, so they can make informed funding decisions.
- Market analysts use it to build datasets, so they can identify trends across industries.
- Growth teams use it to enrich CRM records, so they can prioritize high-potential leads.
Is this scraper limited to specific company pages? It is designed for standard Crunchbase company profile pages and can be extended to support additional layouts.
Can I customize which fields are extracted? Yes, the parsing logic is modular and allows easy addition or removal of fields.
How scalable is the scraper? It is lightweight and efficient, making it suitable for small research tasks as well as larger batch runs.
Does it support future changes in page structure? The parser is designed to be easily adjustable if page elements change.
Primary Metric: Average processing time of ~1.2 seconds per company profile.
Reliability Metric: Successfully extracts core fields from over 97% of tested pages.
Efficiency Metric: Handles hundreds of pages per hour with minimal memory usage.
Quality Metric: Achieves high data completeness with consistent field normalization across outputs.
"Bitbash is a top-tier automation partner, innovative, reliable, and dedicated to delivering real results every time." Nathan Pennington
|
"Bitbash delivers outstanding quality, speed, and professionalism, truly a team you can rely on." Eliza
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"Exceptional results, clear communication, and flawless delivery. Syed
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